With the development of the cellular network technology from the 4th-Generation (4G) to the 5th-Generation (5G), in 5G's standard, the academia and the industry have formed a general consensus that as an important system indicator, the system capacity of 5G should be enhanced by 1000 times than that of 4G. To this end, the user's data rate can be enhanced from three aspects: spectrum efficiency, available bandwidth, and base station's dense deployment and cellular network's heterogeneity. Among them, the base station's dense deployment means deploying more base stations to reduce the coverage and load of each base station, thus providing more resource to user, and then the use's data rate can be enhanced. The implementation of the deployment of a heterogeneous cellular network is to deploy a large number of low-cost small base stations in the traditional macro-cell, and to migrate some users from the macro-cell to these small cells, i.e. these small base stations, which can reduce the loads of the macro base stations, and increase the amount of the resources allocated to user. Thus a heterogeneous network is formed. These small base stations may be micro base stations, pico base stations or femto base stations, which have the same licensed spectrum as that of the macro base stations, or the WiFi access points which set up in the unlicensed spectrum. By increasing the density of the base stations, the large scale deployment of small base stations improves the system capacity and realizes the spectrum reuse, meanwhile, the targeted deployment of small base stations could solve the user association problem in the edge area or the non-covered area of the macro base stations
For each user, it has to select one base station to associate with, which is called user association. The user association also determines the load of each base station in a heterogeneous cellular network, and is a way to realize the efficient resource management. Therefore, the user association is crucial in heterogeneous cellular network. However, comparing to the use association in traditional cellular network, the user association in heterogeneous cellular network is more complex, for the base stations in heterogeneous cellular network are different in terms of transmission power, number of antennas and spectrum, and different types of base station often coexist.
In prior art, there already have many researches concerning to user association in heterogeneous cellular network. The most common method is to model the user association as an optimization problem, then to use optimization theory and algorithms to find the best association strategy. a variable of {0,1} is employed to express the relationship of user and base station, and based on which, a utility function is created, and then the user association is converted into the maximization of the utility function. The specific approach is to model the user association as an integer programming problem, solve this integer programming offline, and then get the optimal association solution. Since the integer programming problem has a integer variable {0,1}, such problem is usually taken as a NP-hard problem. Therefore, it is necessary to design an optimal solution or sub-optimal solution. Relaxation theory and Lagrange duality are typical methods to solve the NP-hard problem. In addition, user association and fairness are often joint considered. The specific approach is to choose a proportional fairness function as the utility function of the user association. The proportional fairness function is a logarithmic function. However, the method has several shortcomings as follows:
(1), Applying the above method in the real heterogeneous cellular network is almost impractical. Firstly, the above method requires to know a large amount of accurate information about the user and the base station in advance, such as the number of users of the whole network, the location of each user, and the each user's data rate, etc. Due to the dynamic and mobility of the cellular network, users are randomly arrived, thus little of such kind of accurate information can be obtained in advance. Secondly, the above algorithm is offline and runs slowly, but the cellular network needs the new arriving users to quickly access, it is obvious that the method is not real-time and not applicable.
(2), The above method do not take the limitation of the base station's backhaul capacity into account when considering the constraints. However, in reality, due to the rapid growth of wireless data traffic and wireless devices, the backhaul capacity has already become a bottleneck to the resource's utilization. When associating a user to a base station, it is necessary to add the backhaul capacity to the constraints.
Therefore, the research emphasis is how to provide a effective user association method under heterogeneous cellular network to guarantee the service demand of users and network performance.